mantel_test: Mantel test
| mantel_test | R Documentation |
Mantel test
Description
This version of the Mantel test supports asymmetric matrices and multiple partial-Mantel controls, a combination of features that is not possible using other widely available Mantel functions such as mantel.partial.
Usage
mantel_test(
x,
y,
z = NULL,
nperm = 999,
method = "pearson",
alternative = c("two.sided", "less", "greater")
)
Arguments
x, y |
Square matrices (can be asymmetric). |
z |
Optional list of one or more square control matrices if partial Mantel is desired. |
nperm |
Number of random permutations to perform (positive integer). |
method |
Correlation method (see cor for details). |
alternative |
A character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". |
Value
A list with the following components:
'stat': The correlation coefficient between
xandy, measured on the data provided. This will be a partial correlation ifzis specified.'quantile': The quantile of the observed stat in the null distribution.
'p.value': Significance, derived from the combination of
quantileandalternative.'perm': A vector of null correlations based on permuted data.
Examples
# A convenience function to generate symmetric matrices:
sym_matrix <- function(x){
n <- which(cumsum(1:100) == length(x)) + 1
m <- matrix(0, n, n)
m[lower.tri(m)] <- x
m[upper.tri(m)] <- t(m)[upper.tri(t(m))]
m
}
# Simulate some example data:
g <- runif(45)
w <- runif(45)
d <- runif(45)
e <- sample(0:1, 45, T)
G <- sym_matrix(g) # e.g. a genetic matrix
W <- sym_matrix(w) # e.g. a wind matrix
D <- sym_matrix(d) # e.g. a distance matrix
E <- sym_matrix(e) # e.g. an environment matrix
# Basic function usage:
mantel_test(G, W) # simple first-order Mantel
mantel_test(G, W, list(D, E)) # partial Mantel
mantel_test(G, W, method = "kendall") # use of alternative test statistic
# Demonstrate that the function matches vegan::mantel.partial output:
# (using only symmetric matrices, and just one control variable, since
# vegan does not work with asymmetric matrices or multiple controls)
a <- mantel_test(G, W, list(D), nperm = 99999)
b <- vegan::mantel.partial(G, W, D, permutations = 99999)
c(a$stat, b$statistic)
c(1 - a$quantile, b$signif) # will differ slightly due to randomization
